Why Release a Large Language Model?
We believe the creation and open source release of a large language model is a net good to AI safety. We explain why.
We believe the creation and open source release of a large language model is a net good to AI safety. We explain why.
Using eval harness, we can deduce the sizes of OpenAI API models from their performance.
We evaluate different fewshot prompts on GPT-3 to see how it changes performance.
We tuned GPT-Neo on eval harness tasks to see how it would change its performance.
An ablation of activation functions in GPT-like autoregressive language models.
Rotary Positional Embedding (RoPE) is a new type of position encoding that unifies absolute and relative approaches. We put it to the test.